Search results for "Hilbert"

showing 10 items of 331 documents

Quantum like modelling of decision making: quantifying uncertainty with the aid of the Heisenberg-Robertson inequality

2018

This paper contributes to quantum-like modeling of decision making (DM) under uncertainty through application of Heisenberg’s uncertainty principle (in the form of the Robertson inequality). In this paper we apply this instrument to quantify uncertainty in DM performed by quantum-like agents. As an example, we apply the Heisenberg uncertainty principle to the determination of mutual interrelation of uncertainties for “incompatible questions” used to be asked in political opinion pools. We also consider the problem of representation of decision problems, e.g., in the form of questions, by Hermitian operators, commuting and noncommuting, corresponding to compatible and incompatible questions …

Compatible and incompatible questionPsychology (all)Uncertainty principleInequalityComputer sciencemedia_common.quotation_subjectMental stateHeisenberg uncertainty principle050105 experimental psychology03 medical and health sciencessymbols.namesake0302 clinical medicine0501 psychology and cognitive sciencesQuantumGeneral Psychologymedia_commonApplied Mathematics05 social sciencesHilbert spaceObservableDecision problemOrder effect16. Peace & justiceHermitian matrixMental statesymbolsDecision makingMathematical economics030217 neurology & neurosurgery
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An Innovative Ambient Identification Method

2020

Ambient modal identification, also known as Operational Modal Analysis (OMA), aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on appl…

Complex representationComputer scienceControl engineeringContext (language use)Operational Modal Analysis Hilbert Transform Analytical.Identification (information)Operational Modal Analysissymbols.namesakeModalsymbolsHilbert transformTime domainSettore ICAR/08 - Scienza Delle CostruzioniRepresentation (mathematics)
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Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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Fast fringe pattern phase demodulation using FIR Hilbert transformers

2016

This paper suggests the use of FIR Hilbert transformers to extract the phase of fringe patterns. This method is computationally faster than any known spatial method that produces wrapped phase maps. Also, the algorithm does not require any parameters to be adjusted which are dependent upon the specific fringe pattern that is being processed, or upon the particular setup of the optical fringe projection system that is being used. It is therefore particularly suitable for full algorithmic automation. The accuracy and validity of the suggested method has been tested using both computer-generated and real fringe patterns. This novel algorithm has been proposed for its advantages in terms of com…

Computer science02 engineering and technology01 natural sciencesGeneralLiterature_MISCELLANEOUSQA76Structured-light 3D scannerlaw.invention010309 opticssymbols.namesakeOpticslaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringDemodulationElectrical and Electronic EngineeringPhysical and Theoretical ChemistryTransformerbusiness.industryAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsTAFringe patternsymbols020201 artificial intelligence & image processingHilbert transformbusinessOptics Communications
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Optimizing Kernel Ridge Regression for Remote Sensing Problems

2018

Kernel methods have been very successful in remote sensing problems because of their ability to deal with high dimensional non-linear data. However, they are computationally expensive to train when a large amount of samples are used. In this context, while the amount of available remote sensing data has constantly increased, the size of training sets in kernel methods is usually restricted to few thousand samples. In this work, we modified the kernel ridge regression (KRR) training procedure to deal with large scale datasets. In addition, the basis functions in the reproducing kernel Hilbert space are defined as parameters to be also optimized during the training process. This extends the n…

Computer science0211 other engineering and technologiesHyperspectral imagingContext (language use)Basis function02 engineering and technology01 natural sciencesData set010104 statistics & probabilityKernel (linear algebra)Kernel methodKernel (statistics)Radial basis function kernel0101 mathematics021101 geological & geomatics engineeringReproducing kernel Hilbert spaceRemote sensingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Intertwining operators between different Hilbert spaces: connection with frames

2009

In this paper we generalize a strategy recently proposed by the author concerning intertwining operators. In particular we discuss the possibility of extending our previous results in such a way to construct (almost) isospectral self-adjoint operators living in different Hilbert spaces. Many examples are discussed in details. Many of them arise from the theory of frames in Hilbert spaces, others from the so-called g-frames.

Computer scienceHilbert spaceFOS: Physical sciencesStatistical and Nonlinear PhysicsMathematical Physics (math-ph)Operator theoryConnection (mathematics)Mathematical OperatorsAlgebrasymbols.namesakeIntertwining operatorsIsospectralOperator (computer programming)Linear algebrasymbolsMathematics::Metric GeometryFrameSettore MAT/07 - Fisica MatematicaEigenvalues and eigenvectorsMathematical Physics
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A novel identification procedure from ambient vibration data

2020

AbstractAmbient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method b…

Computer scienceMechanical Engineering020101 civil engineeringContext (language use)02 engineering and technologyOperational modal analysisCondensed Matter PhysicsHilbert transform0201 civil engineeringVibrationsymbols.namesakeIdentification (information)Operational Modal Analysis020303 mechanical engineering & transportsModal0203 mechanical engineeringCorrelation functionMechanics of MaterialssymbolsAnalytical signalHilbert transformTime domainRepresentation (mathematics)AlgorithmMeccanica
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Automatic fringe pattern enhancement using truly adaptive period-guided bidimensional empirical mode decomposition.

2020

Fringe patterns encode the information about the result of a measurement performed via widely used optical full-field testing methods, e.g., interferometry, digital holographic microscopy, moiré techniques, structured illumination etc. Affected by the optical setup, changing environment and the sample itself fringe patterns are often corrupted with substantial noise, strong and uneven background illumination and exhibit low contrast. Fringe pattern enhancement, i.e., noise minimization and background term removal, at the pre-processing stage prior to the phase map calculation (for the measurement result decoding) is therefore essential to minimize the jeopardizing effect the mentioned error…

Computer sciencePhase contrast microscopyStructured illumination microscopy02 engineering and technology01 natural sciencesHilbert–Huang transformlaw.invention010309 opticsOpticslaw0103 physical sciencesbusiness.industrySignal reconstructionVDP::Technology: 500Moiré patternFilter (signal processing)021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsInterferometryVDP::Teknologi: 500Digital holographic microscopySpatial frequencySpeckle imaging0210 nano-technologybusinessAlgorithmOptics express
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Tempo Induction from Music Recordings Using Ensemble Empirical Mode Decomposition Analysis

2011

Tempo and beat are among the most important features of Western music. Owing to the perceptual nature of tempo, its automatic analysis and extraction remains a difficult task for a large variety of music genres. Western music notation represents musical events using a hierarchical metrical structure distinguishing different time scales. This hierarchy is often modeled using three levels: the tatum, the tactus, and the measure. The tatum represents the shortest durational value in music that is not just an accidental phenomenon (Bilmes 1993). The tactus period is the most perceptually prominent period, and is the period at which most humans would tap their feet in time with the music (Lerdah…

Computer scienceSpeech recognitionmedia_common.quotation_subjectMusicalNotationHilbert–Huang transformComputer Science ApplicationsRhythmAudio editing softwarePerceptionMedia TechnologyMusic information retrievalBeat (music)Musicmedia_commonComputer Music Journal
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Adaptive Threshold, Wavelet and Hilbert Transform for QRS Detection in Electrocardiogram Signals

2017

This paper combines Hilbert and Wavelet transforms and an adaptive threshold technique to detect the QRS complex of electrocardiogram signals. The method is performed in a window framework. First, the Wavelet transform is applied to the ECG signal to remove noise. Next, the Hilbert transform is applied to detect dominant peak points in the signal. Finally, the adaptive threshold technique is applied to detect R-peaks, Q, and S points. The performance of the algorithm is evaluated against the MIT-BIH arrhythmia database, and the numerical results indicated significant detection accuracy.

Computer sciencebusiness.industryNoise (signal processing)010401 analytical chemistryWavelet transformPattern recognition02 engineering and technology01 natural sciencesSignal0104 chemical sciencessymbols.namesakeQRS complexWavelet0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingHilbert transformArtificial intelligenceEcg signalbusiness
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